Veriff, a global identity verification (IDV) provider, today announced significant updates to its fully automated IDV product. The solution uses advanced machine learning to enable a 100% automated identity verification process with zero human involvement.
With the enhanced IDV solution, customers have access to a fast method for validating user identities while providing more in-depth insights related to the session to enable organizations to make better-informed onboarding decisions. The solution has been optimized for decision speed, providing an output in five seconds, and the highest conversion rate for onboarding new customers, making the solution a great fit for risk-tolerant businesses.
Building on the earlier iterations, the new solution has a faster response time, and each verification session has a decision, decision score, and more insights. These insights show in detail what happened in the verification session, providing information points that customers can use to build their own onboarding decision-making.
"This solution is ideal for businesses that require the fastest speed, highest conversion, and detailed session insights to provide their customers an extra layer of security," said Suvrat Joshi, Senior Vice President of Product at Veriff. "The great news for all our customers is that the automation advancements made to the fully automatic solution also enhance Veriff's core identity verification offering."
To better serve their customers' unique needs, Veriff offers two approaches to Identity and Document Verification: a fully automated solution or a hybrid solution. The automation advancements made to the core IDV technology enhance both fully automatic as well as the hybrid offering further benefiting all our customers. The hybrid option is highly automated but unlike the fully automated solution, it is supported by the reassurance of highly trained verification specialists. It has greater flexibility and offers higher fraud prevention and accuracy as well as more risk insights. Learn more here.